[1]肖梅,张雷,寇雯玉,等.一种新的边缘检测算法研究[J].郑州大学学报(工学版),2012,33(04):86.[doi:10.3969/j.issn.1671-6833.2012.04.020]
　XIAO Mei,ZHANG Lei,KOU WenYu,et al.A Novel Edge Detection Method[J].Journal of Zhengzhou University (Engineering Science),2012,33(04):86.[doi:10.3969/j.issn.1671-6833.2012.04.020]
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一种新的边缘检测算法研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33卷
期数:
2012年04期
页码:
86
栏目:
出版日期:
2012-07-10

文章信息/Info

Title:
A Novel Edge Detection Method
作者:
肖梅; 张雷; 寇雯玉; 等.
长安大学汽车学院汽车运输安全保障技术交通行业重点实验室,陕西西安,710064, 长安大学汽车学院汽车运输安全保障技术交通行业重点实验室,陕西西安,710064, 长安大学汽车学院汽车运输安全保障技术交通行业重点实验室,陕西西安,710064, 长安大学汽车学院汽车运输安全保障技术交通行业重点实验室,陕西西安,710064, 长安大学汽车学院汽车运输安全保障技术交通行业重点实验室,陕西西安,710064
Author(s):
XIAO Mei; ZHANG Lei; KOU WenYu; etc;
Key l.nboratory of Automobile Transportation Safety Contro! Technology of Ministry Communication, School of Automobile.Chang’an University,Xi’an 710064,China
关键词:
自适应神经模糊推理系统;  边缘检测;  目标函数
Keywords:
adaptive neuro-fuzzy inference ;  system edge detection;  objective function
分类号:
TG143.7
DOI:
10.3969/j.issn.1671-6833.2012.04.020
摘要:
为了提高边缘检测的运行效率和检测精度,提出了一种新的边缘检测算法,该算法由一个自适应神经模糊推理系统和一个后处理程序组成.选取与边缘方向和梯度双重信息相关的4个目标函数作为自适应神经模糊推理系统的输入,采用计算机合成图像对自适应神经模糊推理系统进行训练.运用一个后处理程序,判断自适应神经模糊推理系统的输出值是否小于门限值,若小于则该像素点为边缘点.仿真实验表明,该方法边缘检测效果优于传统方法和当前文献报道方法.
Abstract:
In order to reduce the impact of parameters on edge detection, we presenl a novel edge detection indigital images, The proposed method consists of an adaptive neural fuzzy inference system and a post-process.ing. We selected the 4 objective functions related to edge direction and gradient magnitude as the adaptive neural fuzzy inference system inputs. The input image and the target image used for training adaptive neural fuzzyinference system were synthesized by the computer. A post-processing procedure was applied to determinewhether the point was an edge point by using a fixed threshold compared with the adaptive neural fuzzy infer.ence system output value. The proposed edge detector is tested on popular images and also compared with popular edge detectors from the literature. Experimental results show that the proposed edge detector exhibitsmuch better performance than the competing operators and may efficiently be used for the detection of edges indigital images.

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更新日期/Last Update: 1900-01-01